add ignore pyc files; quant test

.gitignore

 *.egg-info
+*.pyc
 build/
 ./dist/

paddleslim/quant/test/models/resnet.py

@@ -27,7 +27,7 @@ class ResNet():
         self.layers = layers
         self.prefix_name = prefix_name
 
-    def net(self, input, class_dim=1000, conv1_name='conv1', fc_name=None):
+    def net(self, input, class_dim=1000, conv1_name='conv1', fc_name='res_fc'):
         layers = self.layers
         prefix_name = self.prefix_name if self.prefix_name is '' else self.prefix_name + '_'
         supported_layers = [34, 50, 101, 152]

paddleslim/quant/test/quanter_test.py

@@ -189,7 +189,7 @@ def train(args):
         'activation_quantize_type': 'abs_max',
         # weight quantize bit num, default is 8
         'weight_bits': 8,
-        # activation quantize bit num， default is 8
+        # activation quantize bit num, default is 8
         'activation_bits': 8,
         # op of name_scope in not_quant_pattern list, will not quantized
         'not_quant_pattern': ['skip_quant'],
@@ -199,7 +199,7 @@ def train(args):
         'dtype': 'int8',
         # window size for 'range_abs_max' quantization. defaulf is 10000
         'window_size': 10000,
-        # The decay coefficient of moving average，default is 0.9
+        # The decay coefficient of moving average, default is 0.9
         'moving_rate': 0.9,
         # if set quant_weight_only True, then only quantize parameters of layers which need quantization,
         # and insert anti-quantization op for parameters of these layers.

paddleslim/quant/test/run_quant.sh

 #!/usr/bin/env bash
+source activate py27_paddle1.6
 
 #MobileNet v1:
 python quanter_test.py \
     --model=MobileNet \
-    --pretrained_fp32_model=${pretrain_dir}/MobileNetV1_pretrained \
+    --pretrained_fp32_model='../../pretrain/MobileNetV1_pretrained/' \
     --use_gpu=True \
-    --data_dir=${data_dir} \
+    --data_dir='/home/ssd8/wsz/tianfei01/traindata/imagenet/' \
     --batch_size=256 \
     --total_images=1281167 \
     --class_dim=1000 \
@@ -17,7 +18,6 @@ python quanter_test.py \
     --act_quant_type=abs_max \
     --wt_quant_type=abs_max
 
-
 #ResNet50:
 #python quanter_test.py \
 #       --model=ResNet50 \